Open AccessAdaptive decentralised control for large‐scale non‐linear non‐strict‐feedback interconnected systems with time‐varying asymmetric output constraints and dead‐zone inputs
Author(s) -
Wang XiaoMei,
Feng ZhiGuang,
Zhang GuangJu,
Niu Ben,
Yang Dong,
Hayat Tasawar,
Alsaadi Fuad E.
Publication year - 2020
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2019.0283
Subject(s) - control theory (sociology) , backstepping , dead zone , lyapunov function , controller (irrigation) , computer science , bounded function , constraint (computer aided design) , stability (learning theory) , adaptive control , nonlinear system , mathematics , control (management) , artificial intelligence , mathematical analysis , oceanography , physics , geometry , quantum mechanics , machine learning , agronomy , biology , geology
This study investigatesthe neural‐network (NN)‐based adaptive decentralised controller design issue for a class of large‐scale non‐linear non‐strict‐feedback interconnected systems with time‐varying asymmetric output constraints and dead‐zone inputs. The existences of the non‐strict‐feedback structure, time‐varying asymmetric output constraints, and dead‐zone inputs lead to the construction of the controller of each subsystem is very difficult. By applying the inherent property of Gaussian functions employed in radical basis function NNs, the non‐strict‐feedback structure is skillfully handled, and the adaptive backstepping method is used to construct the desired controllers of all subsystems. Furthermore, Lyapunov stability analysis shows that all the signals of the closed‐loop system are ultimately bounded, and each subsystem output can converge to an arbitrarily small and predefined time‐varying range with the corresponding constraint is always satisfied by employing a barrier Lyapunov function. Finally, simulation results based on a practical example prove the effectiveness of the proposed design strategy.